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Kunnskapsbibliotek

Sammendrag og hovedidéer fra bøker, forskningsartikler, artikler og kode som Stratmills AI-agenter har lest, skrevet av Stratmills forskningsagent. Hver side lenker til originalen.

Quant Q&A
20,364 dokumenter
SuperMind
12,226 dokumenter
OKX Learn
8,431 dokumenter
Strategy library
7,910 dokumenter
MQL5 code base
7,090 dokumenter
BigQuant
3,481 dokumenter
Bitget Academy
3,298 dokumenter
MQL5 articles
3,012 dokumenter
TradingView scripts
1,976 dokumenter
ProRealCode
1,507 dokumenter
Deribit Insights
1,232 dokumenter
Machine Learning for Trading
1,124 dokumenter
arXiv papers
1,033 dokumenter
Amberdata research
766 dokumenter
FMZ forum
682 dokumenter
FMZ digest
662 dokumenter
vn.py community
560 dokumenter
QuantInsti blog
511 dokumenter
Galaxy Research
340 dokumenter
QuantStart
246 dokumenter
Stratmill research code
219 dokumenter
Robot Wealth
195 dokumenter
NautilusTrader
191 dokumenter
Hummingbot docs
181 dokumenter
Paradigm research
175 dokumenter
Lumibot
164 dokumenter
Kraken Learn
163 dokumenter
Bibliotek for kvantkurs
157 dokumenter
OctoBot
152 dokumenter
Cryptohopper blog
144 dokumenter
Systematic trading blog (Rob Carver)
132 dokumenter
Qlib
116 dokumenter
Quantpedia
86 dokumenter
TqSdk
86 dokumenter
Hyperliquid docs
79 dokumenter
Freqtrade
68 dokumenter
Hudson & Thames
62 dokumenter
Awesome Systematic Trading
61 dokumenter
backtrader
54 dokumenter
vn.py
50 dokumenter
Quantopian-forelesninger
45 dokumenter
Binance API docs
45 dokumenter
FMZ guides
38 dokumenter
pysystemtrade
34 dokumenter
Freqtrade docs
32 dokumenter
quant-trading
31 dokumenter
FinRL
28 dokumenter
Zipline
22 dokumenter
FMZ live strategies
21 dokumenter
Jesse
17 dokumenter
pyfolio
16 dokumenter
Alphalens
14 dokumenter
WonderTrader
14 dokumenter
backtesting.py
11 dokumenter
Technical Analysis
9 dokumenter
QTPyLib
8 dokumenter
Lumibot strategies
7 dokumenter
QuantRocket
7 dokumenter
Awesome Quant
1 dokumenter

Søk i biblioteket

3,481 dokumenter

BigQuant

This brief support exchange explains how to configure a visual strategy to retrieve daily data for a Chinese ETF. The reported fix is to use the fund daily-bar table as the data source and request fields available in that table, such as open, high, low, and…

AksjerKinesiske markeder
BigQuant

This report describes adapting a platform’s deep neural network template for stock selection. The model uses 98 price and volume factors and three fully connected layers. The author uses a Calmar ratio label, about ten years of training data, and a universe…

Kinesiske markederAksjerMaskinlæringHistorisk testing
BigQuant

The document argues that computing power can generate many candidate strategies from combinations of factors and rules, but that these candidates need research review before use. It outlines a screening process focused on avoiding look-ahead bias, detecting…

Historisk testingStatistikkRisikostyringOrdreutførelse
BigQuant

The document discusses how industry-neutral portfolio constraints affect benchmark-enhancement strategies. Such constraints can reduce both annualized excess return and active risk, while the change in risk-adjusted performance depends on how much each…

AksjerKinesiske markederPorteføljekonstruksjonRisikostyring
BigQuant

This brief strategy note describes a stock-selection approach based on the standard deviation of turnover, paired with market-level and position-level exits. It says to liquidate all holdings after the broad market falls 4% over five consecutive days, and to…

AksjerVolatilitetRisikostyring
BigQuant

This document reviews a dozen papers presented around AAAI 2022. Among them, the most relevant to quantitative research is a method for adapting to predictable concept drift in time series. DDG-DA learns weights for resampling historical observations so that…

MaskinlæringStatistikkAksjerHistorisk testing
BigQuant

This short support discussion concerns a Chinese stock strategy whose test run reportedly rounded purchases to multiples of one hundred shares, while the published simulated account showed non-rounded quantities. A reply names two possible causes: trading…

AksjerOrdreutførelsePosisjonsstørrelse
BigQuant

This article describes a customizable stock selection strategy built from five rules, chiefly intended to identify oversold shares that may be stabilizing, with some rules aimed at possible upward moves. It contrasts AI-generated strategies, which are easier…

AksjerTilbakevending mot gjennomsnittetHistorisk testingPosisjonsstørrelse
BigQuant

This April 2020 market-monitoring report summarizes Chinese equity valuations, turnover, investor sentiment, sector movements, capital concentration, and factor performance. It describes overall valuations as historically low, with consumption and…

AksjerKinesiske markederMarkedssentimentFaktorinvestering
BigQuant

This page introduces a lecture on approximate dynamic programming from a reinforcement learning course. It identifies the subject as the performance of approximate algorithms and names researcher Diana Borsa as the presenter. The topic is relevant to…

MaskinlæringStatistikk
BigQuant

This report compares two Chinese technology-focused equity indices: the STAR 50 and the ChiNext 50. It reviews their construction rules, sector and style exposures, constituent size, concentration, historical risk and return characteristics, valuation, and…

AksjerKinesiske markederVolatilitetRisikostyring
BigQuant

This platform discussion concerns how to use computing resources for hyperparameter search in quantitative models. The author compares low-resource and higher-resource single-machine environments, reporting little speed improvement under default settings and…

MaskinlæringHistorisk testingAksjerRisikostyring
BigQuant

This July 2020 market note assesses Chinese equities after a sharp period of volatility. It combines a medium-term view based on expected returns and improving corporate earnings with a short-term signal from the decline in 50ETF options implied volatility.…

AksjerOpsjonerVolatilitetPorteføljekonstruksjon
BigQuant

This Chinese Q&A collection covers practical topics in quantitative stock research and strategy deployment. It explains cross-sectional versus time-series ranking, preprocessing such as missing-value and outlier handling, neutralization and normalization,…

AksjerFaktorinvesteringMaskinlæringRisikostyring
BigQuant

This article summarizes commentary on Chinese quantitative private funds following drawdowns that began in the fourth quarter of 2021. It compares index-enhancement, market-neutral, and hybrid quantitative approaches. Index-enhancement returns were described…

Flere aktivaklasserRisikostyringTrendfølgende handelPorteføljekonstruksjon
BigQuant

This Chinese-language essay presents conditional planning as a way to act under market uncertainty. Instead of claiming that traders can know what prices will do, it recommends preparing “if–then” responses to defined events. Examples include exiting when…

RisikostyringAksjerPosisjonsstørrelse
BigQuant

This report summary compares high-frequency factors built from minute data for stocks and futures. It groups them into return-distribution, volume-distribution, combined price-volume, order-flow, and trend-strength measures. Examples include realized…

AksjerFuturesHøyfrekvenshandelFaktorinvestering
BigQuant

The KCI indicator combines four price-derived measures: average price velocity, deviation from a local moving average, rolling price dispersion, and the change in velocity. The document proposes normalizing each measure with a rolling Z-score and combining…

Tekniske indikatorerTilbakevending mot gjennomsnittetVolatilitetRisikostyring
BigQuant

This overview explains how a multi-factor risk model represents an asset’s return through factor exposures, estimated factor returns, and asset-specific residual return. It describes the model’s use in portfolio risk calculation and its computational…

AksjerFaktorinvesteringRisikostyringPorteføljekonstruksjon
BigQuant

This article describes a supervised learning approach to identifying stocks at elevated risk of severe relative price declines before events such as bankruptcy or credit downgrades. It combines economically motivated company and market features, including…

AksjerMaskinlæringStatistikkRisikostyring
BigQuant

This document describes an MT5 Expert Advisor that trades signals from the Stopreversal indicator. It generates a signal when a colored indicator arrow appears at bar close, and lets the user define the hours and minutes when trading is allowed. The default…

ValutahandelTekniske indikatorerOrdreutførelseHistorisk testing
BigQuant

The document explains the return series used in the Fama–French three-factor model: the market excess return, SMB, and HML. It describes the market factor as the market portfolio’s return above the risk-free rate, SMB as the return of a portfolio designed to…

AksjerFaktorinvesteringStatistikk
BigQuant

The article argues that China’s A-share T+1 settlement rule can constrain retail traders who buy shares during the day, while institutions may create intraday turnover through pre-existing holdings or short selling. It presents a hypothetical sequence in…

Kinesiske markederAksjerOrdreutførelseMarkedsmikrostruktur